361 results about "Information needs" patented technology

The invention discloses a method for generating and constructing a database test knowledge base based on an open source large language model and retrieval enhancement, and relates to the technical field of database testing, and the method comprises the steps: building a local deployment system on a local computer system or server, and achieving the efficient local operation of the open source large language model and the stable output of language processing service; on a local computer system or a server, a retrieval enhancement generation framework is constructed, and accurate knowledge support and reliable content output are provided for local language processing service by integrating multi-modal knowledge, optimizing retrieval and generation processes and guaranteeing safety and compliance; on a local computer system or a server, a personalized database knowledge base is built, database related information is collected and processed from multiple channels and is output in an adaptive form, and the specified information requirement of local personalized language processing service is met. According to the method, efficient and stable operation of the open source large language model is realized, accurate and reliable language processing output is realized, and personalized services meet specific requirements.

The invention relates to the technical field of artificial intelligence, in particular to an agent dynamic decision network generation method based on reinforcement learning. The method comprises the following steps: receiving information demand data input by a user; performing feature analysis on the information demand data, and extracting a business target, a constraint condition and a key parameter to obtain an information demand analysis result; identifying a task flow corresponding to the information demand analysis result, and matching an API call chain according to the task flow to obtain a task demand technology blueprint; generating an agent workflow according to the task demand technology blueprint by using a preset dynamic workflow engine; performing context analysis on the language demand analysis result to obtain context information; the agent workflow is divided into ultra-long thinking chains based on context information. In conclusion, through the reinforcement learning technology, the intelligent agent can be automatically generated and continuously optimized according to user requirements, and efficient decision making and dynamic adaptation of complex service scenes are supported.

The invention discloses a multi-agent dynamic arrangement method based on multi-modal analysis and adaptive retrieval, and relates to the technical field of artificial intelligence and information retrieval. Comprising the steps of S1, converting a text, an image, structured data and voice content input by a user into a unified multi-mode semantic representation, S2, converting the unified multi-mode semantic representation into a specific execution process, and S3, automatically scheduling a reasoning agent, a knowledge obtaining agent and an execution agent according to DAG nodes, task elements and available resources, and obtaining the task elements and the execution agent according to the reasoning agent, the knowledge obtaining agent and the execution agent. S4, after task process construction and agent arrangement are completed, dynamic retrieval, evidence convergence and strategy optimization are carried out on information requirements related to a user task, so that a reasoning agent obtains complete knowledge support with consistent context, and S5, knowledge evidence is combined with a task process, so that the task process is completed. The method comprises the following steps: step S6, implementing problem solving, strategy generation and task closed-loop execution through a reasoning agent, step S6, performing actual operation on a target task by an execution agent according to an executable instruction sequence output by the reasoning agent, and outputting a result, and step S7, performing result verification according to an output result returned by the execution agent, and the correctness, integrity and consistency of an output result are examined through rule verification, model evaluation and evidence alignment.

The invention belongs to the technical field of artificial intelligence and multi-modal large model reasoning enhancement, and discloses a multi-modal retrieval enhancement generation method based on gradual group relative strategy optimization. A step-by-step reasoning track construction mechanism is introduced, an original problem is disassembled into a plurality of sub-problems, and in each step, a new retrieval query is autonomously generated in combination with reasoning history and current information requirements, and a most appropriate knowledge source is selected for evidence retrieval; and in the reasoning process, each step of decision and answer obtains a fine-grained reward signal. According to the method, a group relative strategy optimization method is adopted, the query quality of each reasoning step, the knowledge base routing accuracy, the answer content format compliance and the final answer accuracy are used as step-by-step rewards for joint modeling, and model parameters are optimized through global and local multiple feedback signals. The method is remarkably superior to the existing similar technology in tasks such as multi-class multi-modal open domain question answering and complex reasoning, and has excellent answer accuracy, retrieval efficiency and multi-modal adaptive capacity.

The invention discloses an intelligent question answering system and method based on question decomposition and community semantic search. According to the method, firstly, a complex question is decomposed into a plurality of single-hop sub-questions through an original loop question decomposition technology, then information needed for answering each sub-question is obtained based on communities in a vector retrieval knowledge graph, and the sub-questions are answered by using a large language model. And finally, generating a final question and answer for the original complex question by combining the LLM with the answers of all the sub-questions. Compared with other methods in the industry, the method has the advantages that the information integration capability is remarkably improved, information fragmentation is avoided through community-level search and abstract generation, and high-quality and logically consistent answers are provided. When a complex query is processed, the effect of the method is superior to that of a general method in the industry and is improved by 29% at most; meanwhile, on the basis of ensuring a better question and answer effect, the efficiency is remarkably improved, and on the premise that the effect exceeds that of an existing optimal method GraphRAG, the token consumption is only 3.2% of that of the existing optimal method GraphRAG.

A computing system for progressive virtual assistance in tax applications includes a computing device with processing circuitry configured to implement a tax application virtual assistant program. The processing circuitry is configured to receive a tax-related user query, identify an intent in the query, and select a workflow including operations required for responding to the intent. The processing circuitry is further configured to implement a workflow orchestrator to schedule a sequence of the operations, identify information needed to complete a target operation, and generate and input an information augmentation prompt to a large language model to retrieve the information. The processing circuitry is further configured to receive a response to the information augmentation prompt, generate and input a user query response prompt to the large language model, receive the user query response, and display the user query response in a chat interface.

The invention provides a digital human video generation method and device based on a large model, an intelligent agent, electronic equipment and a storage medium, relates to the technical field of artificial intelligence, in particular to the technical fields of deep learning, the large model, computer vision and the like, and can be applied to scenes such as video live broadcast, advertisement production, e-commerce sales and the like. The digital human video generation method based on the large model comprises the steps that demand information is acquired, the demand information comprises action description information used for describing a specified action video clip, and the action video clip represents a specified action of a target object; processing the demand information by utilizing a language large model to obtain a target script which comprises a target oral playing fragment text matched with the action description information; and processing the target script and the action video clip by using a visual large model to obtain a target video which is used for displaying oral playing of the target object based on the target oral playing clip text in the process of executing the specified action.

The invention relates to the technical field of information processing, and discloses a big data-based information matching management system, which comprises an acquisition module, an attribute analysis module, a multi-dimensional modeling module and a dynamic matching module. The acquisition module acquires a user behavior data set and extracts active information demand features; the attribute analysis module analyzes the real-time updating frequency, the semantic association degree, the historical matching success rate and the data topological structure characteristics of the target information resources; a multi-dimensional modeling module performs heterogeneous modeling on each feature to generate timeliness, semantic association, matching probability feature vectors and topological structure vectors; and the dynamic matching module generates an adaptation degree score and determines an optimal matching object through heterogeneous space projection and feature coupling operation. The system improves the accuracy, real-time performance and efficiency of information matching through multi-dimensional feature processing, topological structure analysis and a dynamic matching algorithm, and is suitable for an accurate information matching scene in a big data environment.

The invention discloses a medical text data synthesis method based on role driving, and relates to the technical field of text data synthesis and artificial intelligence, and the method comprises the following steps: S100, generating an original problem; s200, screening original problems; and S300, synthesizing the medical text data. According to role description and interest content generation, the adaptability to different medical role requirements is enhanced, semantic duplicate removal and correlation evaluation are realized by utilizing a text coding model and a vector database, semantic duplicate content is removed, correlation is accurately evaluated by utilizing a large language model, the data quality and diversity are improved, and the method is suitable for popularization and application. Through generation of variant questions and answers, diversity and practicability of medical text data are enriched. According to the method, the personalization and pertinence of the medical text data are improved, the quality and duplicate removal efficiency of the medical text data are enhanced, the problem types are enriched, the generated content is optimized, and various information requirements of the medical text data are comprehensively covered.

The invention relates to the technical field of information pushing, in particular to a platform user interest recommendation method and system based on artificial intelligence. The method comprises the following steps: acquiring user action data and environment perception data, analyzing the user action data and the environment perception data, and constructing a unified space-time semantic network; according to the unified space-time semantic network, analyzing scene features of the user, and determining a multi-dimensional dynamic scene feature set; and analyzing the multi-dimensional dynamic scene feature set, determining composite scene demand information of the current user, and retrieving and pushing real-time demand information of the user according to the composite scene demand information. According to the method and the device, the perception capability of the pushed information to the user demand scene is improved, the multi-dimensional dynamic adaptation of the pushed information to the platform user is realized, the information pushing accuracy for the platform user is improved, and the composite information demand of the user in a complex scene is met.

The embodiment of the invention provides a method, device and system for constructing an attack graph, and a storage medium, and relates to the technical field of network security. The method comprises the steps that based on a test case knowledge base of a target system, an attack graph information expansion algorithm is executed through a knowledge graph technology, and expanded information is obtained; utilizing the expanded information to construct an attribute attack graph of the target system; and carrying out attack path description on vulnerabilities of the target system based on the attribute attack graph. An attack graph information expansion algorithm is executed through a test case knowledge base based on a target system and by means of a knowledge graph technology, information needed for constructing an attack graph can be obtained, potential attack paths can be mined, the attack graph information is expanded, and then a comprehensive and accurate attribute attack graph is constructed. According to the method, effective description of the vulnerability attack path of the target system is realized, so that the constructed attack graph can reflect the security condition of the network system more truly, more scientific decision support is provided for network security management personnel, and the network security protection effect is improved.

The invention relates to a server test environment automatic monitoring method and system. The method comprises the following steps: acquiring various data in a test environment of a plurality of servers in a specified period, and dividing the data into a training set, a test set and a verification set; the method comprises the following steps of: acquiring various monitored server test environments, inputting the monitored server test environments into a server test environment monitoring model for training, testing and verifying, acquiring various data in the monitored server test environments in real time, inputting the data into the server test environment monitoring model, and outputting monitoring results of the monitored server test environments in real time through the server test environment monitoring model. And the server obtains abnormal information according to the monitoring result, obtains an abnormal position and an abnormal severity degree of the monitoring test environment based on the abnormal information according to whether the abnormal information needs to be processed or not, analyzes an abnormal solution according to the abnormal position and abnormal data, and processes the abnormality based on the obtained abnormal solution. The server test environment monitoring efficiency is effectively improved, and the missed test rate is reduced.

The present disclosure generally relates to generating and / or modifying text using a digital assistant. This disclosure encompasses a system for requesting information before generating text using models based on the type of information needed. This disclosure further encompasses a system for a remote model requesting additional information before generating text. This disclosure encompasses user interfaces for text generation / modification. This disclosure encompasses a system for proofreading text using a model. This disclosure encompasses a system for generating a response to a received communication with operations for updating the generated response.

The embodiment of the invention provides an information acquisition method and device and electronic equipment, and relates to the technical field of computers. The information acquisition method comprises the following steps: acquiring a webpage address of a first webpage; collecting first original webpage information corresponding to the webpage address of the first webpage; according to an information extraction rule, first webpage information is extracted from the first original webpage information, the information extraction rule is data generated through a large language model according to content description information and second original webpage information of a second webpage, and the content description information indicates webpage information needing to be obtained from the webpage. According to the method and the device, the adaptability to variable webpage structures can be improved, and the webpage information extraction efficiency is improved.

The present disclosure generally relates to generating and / or modifying text using a digital assistant. This disclosure encompasses a system for requesting information before generating text using models based on the type of information needed. This disclosure further encompasses a system for a remote model requesting additional information before generating text. This disclosure encompasses user interfaces for text generation / modification. This disclosure encompasses a system for proofreading text using a model. This disclosure encompasses a system for generating a response to a received communication with operations for updating the generated response.

The invention provides an outline content generation method and system combined with natural language processing, and the method comprises the steps: firstly carrying out the medical semantic analysis of a medical question text inputted by a user, obtaining a question feature set, calling a medical literature database interface for retrieval based on the question feature set, and obtaining a matched medical literature knowledge set; extracting medical knowledge units with independent semantics from the literature knowledge set to generate a structured knowledge unit set, performing association matching on the structured knowledge unit set and the question feature set, distributing weights according to question type identifiers and information demand strength parameters to generate a weighted knowledge integration result, and performing knowledge integration on the weighted knowledge integration result; and finally, generating a medical question answering text according to a weighted knowledge integration result, and feeding back the medical question answering text to a user interaction interface for display, so that accurate, comprehensive and personalized medical question answering can be provided for the user, and the question answering quality and the user experience of a medical academic community are improved.

The invention provides a scientific and technical literature question and answer method and system based on self-feedback iterative optimization, and the method comprises the steps: receiving a user question, and generating an initial response through employing a retrieval enhancement generation strategy; taking the initial response as iterative input, and performing multi-dimensional evaluation on the iterative input to obtain structured feedback with a plurality of specific feedbacks; extracting an information demand from the structured feedback, and performing supplementary retrieval according to the information demand to obtain supplementary information; performing progressive information fusion on the supplementary information and the iterative input according to the priority ranking of the specific feedback to obtain an optimized content; verifying and correcting references in the optimized contents to obtain iterative output; and judging whether an iteration termination condition is met or not according to the iteration output, if so, taking the iteration output as a final response, and otherwise, taking the iteration output input as the iteration input to carry out iteration optimization until the final response is obtained. According to the invention, the answering quality of academic answers can be greatly improved.

The embodiment of the invention provides an information processing method and device, a storage medium and a program product. In the embodiment of the invention, after the intelligent customer service enters the trusteeship state, the question information and the subsequent question information received within the validity period of the distributed lock are stored in the message queue as a current batch of question information needing delay processing, the delay processing can give real communication feeling to merchants, and the service experience of the merchants is improved. Furthermore, under the condition that timing of the timing task of the message queue is finished, an AI question and answer service model based on artificial intelligence is called to perform unified reply processing on the question information currently needing delay processing in the message queue, so that target reply information corresponding to the obtained question information is sent to a client of a target merchant; and the target merchant can check the target reply information corresponding to each piece of question information, so that manual customer service is replaced, the labor is saved, and the question processing efficiency is improved.

The invention discloses a traffic knowledge graph automatic generation system and method, relates to the technical field of traffic informatization and smart travel, and aims to solve the problem that an existing traffic information management system is difficult to effectively classify and integrate multi-source heterogeneous data. The system comprises a collection device used for collecting multi-source heterogeneous data in the traffic field and sending the multi-source heterogeneous data to a traffic knowledge graph generation module; the traffic knowledge graph generation module is used for generating and managing a traffic knowledge graph based on the multi-source heterogeneous data and sending the traffic knowledge graph to the server for storage; and the terminal equipment is used for sending an interaction instruction to the traffic knowledge graph generation module and receiving target information generated by the traffic knowledge graph generation module based on the interaction instruction. The traffic knowledge graph automatic generation system provided by the invention is used for carrying out efficient integration and classification on multi-source heterogeneous data so as to meet information requirements of different scenes in a complex traffic environment.

A system and method for an AI-based Automated Software Application Development Platform which intelligently gathers requirements from a business analyst and generates a runnable software application from those requirements. The AI-based platform enables the business analyst with no technical knowledge to visually model their requirements rapidly without requiring any programming Using the abstract requirements architecture and the platform, the analyst creates requirements models for the application's business processes and business tasks for each of the processes, including defining the supporting information needs. The system intelligently assists the user in defining the information needs for each of the business processes and their tasks. Once the requirements models are created by the analyst with the help of the platform, the platform automatically designs and creates an appropriate persistent canonical data model for the application from the defined information needs. The platform then creates a runnable software application. The system also provides a template for the user to input their requirements in descriptive text, and accepts requirements document for applications as written free form text or text documents written in English as input, and in a non-English language that the system automatically translates them into English. The system provides a method for reverse engineering an existing application, including generating a requirements document for the existing application such as a legacy modernization or digital transformation an old applications for redesigning, updating or revising them to accommodate a new requirements set for such applications.

The embodiment of the invention provides a memory information processing method of a large language model and a computer program product, and relates to the technical field of large language models. The method comprises the steps of obtaining interaction request information of a target object, extracting at least one piece of memory information needing to be memorized from the interaction request information based on a large language model, performing classification and importance evaluation on each piece of memory information to obtain category information and an importance score of each piece of memory information, and according to each piece of category information, determining the importance score of each piece of memory information. And determining the expiration duration of each piece of memory information, and storing each piece of memory information, the corresponding category information, the corresponding expiration duration and the corresponding importance score into an active memory pool of the target object. Context management can be carried out by using the memory information, and the context management accuracy of a large language model in a cross-session scene is remarkably improved.

The present disclosure generally relates to generating and / or modifying text using a digital assistant. This disclosure encompasses a system for requesting information before generating text using models based on the type of information needed. This disclosure further encompasses a system for a remote model requesting additional information before generating text. This disclosure encompasses user interfaces for text generation / modification. This disclosure encompasses a system for proofreading text using a model. This disclosure encompasses a system for generating a response to a received communication with operations for updating the generated response.

The invention provides a traffic information release method and system, and belongs to the field of traffic information release, and the method comprises the steps: carrying out the clustering processing of the road condition information of a first region based on a clustering algorithm, and obtaining first clustering data; the first area is an area in which traffic information needs to be published; based on the first clustering data, determining a target publishing strategy for publishing traffic information to a second area, the second area being an area in the first area; and publishing the traffic information to the second area based on the target publishing strategy. According to the traffic information publishing method and system provided by the invention, the accuracy and reliability of traffic information publishing can be improved.

Disclosed are a service demand-driven routing scheduling and dynamic selection method and system for active distribution network. The method includes: evaluating a physical importance index and an information importance index of each service traffic according to a physical influence and an information demand of each issued service traffic, comprehensively taking into account the physical importance index and the information importance index to obtain a comprehensive importance index, and ranking the comprehensive importance index to obtain a ranked service traffic set; quantizing the real-time performance and the reliability of a route link and generating a route distance matrix; inputting the ranked service traffic set and the route distance matrix into a route scheduling optimization model, and generating a route scheduling scheme of the overall service traffic based on a principle of service traffic importance and route path performance matching.

The invention discloses a configuration information pushing method, electronic equipment and a storage medium, and the method comprises the steps: obtaining first configuration information of a local configuration file for at least one configuration item of a target micro-service, and obtaining second configuration information of a configuration center for at least one configuration item of the target micro-service in response to the updating of the local configuration file; comparing the first configuration information with the second configuration information to determine difference information of each configuration item; and pushing each piece of difference information to a configuration center to complete configuration pushing processing. According to the method and the device, the configuration information needing to be pushed, namely the difference information, is determined by comparing the configuration information of the local configuration file and the configuration information of the configuration center, and then the difference information of each configuration item is pushed to the configuration center, so that accurate pushing of each configuration item is completed, configuration pushing of the target micro-service in various scenes is met, the cost is reduced, and the user experience is improved. And the stable operation of the application program is correspondingly improved.

The invention belongs to the technical field of clause analysis, and particularly relates to an insurance clause analysis system based on an AI large model, which comprises an input module, a processor, a network connection end, an analysis submission end and display equipment, and is characterized in that the processor is integrated with an AI technology; the output end of the input module is connected with the processor, the output end of the processor is connected with the display device, the processor is in communication connection with the network connection end, and the analysis submission end is in communication connection with the network connection end. According to the design of the scheme, based on the clamping of the AI technology, insurance terms are usually long in length and complex in content, and manual analysis needs to consume a large amount of time and energy. The AI can process a large number of insurance clause texts in a short time, quickly extract key information, and greatly improve the analysis speed. When a customer or an insurance practitioner needs to know the insurance clause information, the AI system can carry out analysis and feedback in real time, and does not need to queue up to wait for processing like manual work, so that the information requirement of the user can be met in time.

An entangled links mechanism to establish and maintain bipartite temporal intimacy between pairs of computers using an idempotent, reversible token method, which presents no observable external “change” until communication of information needs to occur between the computers and which maintains the potential for “bounded (or unbounded) reversibility” in case the intended information dispatched by a source computational entity is not captured or properly accepted by a destination computational entity. The mechanism enables distributed computers in a network to remain continuously aware of each other's presence; to communicate on a logically nearest neighbor basis in a secure and reliable manner in which packets passed over these links do not conflict with normal traffic or cause the available resources of the link to exceeded; and that atomicity, isolation, and “reversible durability” may be maintained for transactions when perturbations occur.

The invention discloses a multi-satellite planning method and device based on a deep learning neural network and a medium, and the method comprises the steps: obtaining the historical planning data of multi-satellite planning, and obtaining the resource information of the multi-satellite planning deep learning neural network after preprocessing; determining a constraint function as a model constraint condition of the deep learning neural network according to constraint information needing to be considered in multi-satellite planning; marking a flag bit, and selecting a resource information characteristic value as a deep learning neural network input according to an observed target task; according to the observation task satisfaction degree of multi-satellite planning and the satellite load utilization rate, an objective function is determined, and the deep learning neural network is trained; and performing multi-satellite planning by using the trained deep learning neural network. According to the novel multi-satellite planning method based on the deep learning neural network, the multi-satellite planning task can have better redundancy, robustness and task execution capacity, and the multi-satellite planning task requirement of a user can be met more quickly and more accurately.

The invention discloses a method and a device for determining a management strategy of a grounding wire, and a readable storage medium. The method comprises the steps that basic data of a grounding wire are acquired, and the basic data at least comprise one of environment information, operation information and fault information of the position where the grounding wire is located; on the basis of the basic data, monitoring information, demand information and fault information of the ground wire are determined, the monitoring information is used for indicating parameters for monitoring the ground wire, the demand information is used for indicating the demand trend of the ground wire in the future time period, and the fault information is used for indicating faults of the ground wire in the future time period; based on the monitoring information, the demand information and the fault information, a management strategy of the ground wire is determined, and the management strategy is used for representing a rule for performing management operation on the ground wire. The technical problem of single ground wire management is solved.

The invention provides a service optimization method and system based on data of old people, electronic equipment and a storage medium, and belongs to the field of services. The method comprises the following steps: acquiring basic information and demand information of old people and current service information provided by a community; using a K-means clustering algorithm to classify and label the old people based on the basic information and demand information of the old people; and optimizing the service according to the label identifier and the current service information provided by the community. By collecting and sorting the data of the old people and performing classification management, accurate data management is realized, so that accurate work guidance is provided for service personnel, and diversified requirements of the old people can be efficiently and accurately met.